Single domain nanomagnets carry significant potential in several application areas wherein the magnetic fields of the nanomagnetics are used in place of standard electrical currents and data computation. Advanced fabrication and estimation methods have created opportunities for researchers to investigate and understand the phenomena of magnetization in patterned magnetic nanostructures to use them as magnetic recording media for digital storage, magnetoresistive random access memory (MRAM), spintronics for memory technologies, nanomagnetic logic circuits, nanomagnetic processors, next generation computing elements and in the biosciences. One advantage of magnetic information systems is that they consume far less power than standard electrical systems. Also, magnetic memory systems are non-volatile, and as such, they do not lose information during shut down, resulting in a reduced boot-up time upon system restart.
It is known that nanomagnets, magnets smaller than approximately 100 nm, behave as single domain entities. These small nanomagnets can be used to represent states of computing logic such as Boolean logic or an energy minimizing coprocessor. A single domain entity is a nanomagnet with a uniform magnetization state, wherein the dimensions of the magnetic nanostructure are less than the domain wall length. Since magnets only have two possible magnetization states, the magnetization states can be used to represent ones and zeroes similar to typical binary code that is currently used by electronic microprocessors. By placing a series of single domain nanomagnet disks on a silicon substrate, the interactions between the nanomagnets can be exploited to transmit information from input to output.
Magnetic data storage and data computation with nanomagnets depends on the geometric placement of the nanomagnet disks on the silicon substrate. The nature of the interactions between the nanomagnets is controlled by the topology of the placement of the nanomagnets to achieve various logic gates. Thus, the layout is an important factor for accurate data computation utilizing nanomagnets. Any irregularities present in the placement of the nanomagnets with respect to the desired CAD (computer-aided design) base layout may result in computational errors. Hence, inspection of the fabricated nanomagnet assembly for geometric irregularities is vital.
In the prior art, a person, assisted by an image-viewer, analyzes atomic force microscopy (AFM) and/or magnetic force microscopy (MFM) images of a nanomagnet disk array to identify geometric irregularities. AFM and MFM images generally capture images at depths of nanometers. Often, the image-viewer is a microscope and the person must manually examine the nanomagnets to compare them to an expected base layout. This prior art method of analysis is tedious and error prone. While there are some software tools capable of analyzing AFM images, these tools do not provide feedback on how closely the fabricated nanomagnet disk array resembles the base layout.
Additionally, Magnetic force microscopy (MFM) has made it possible for researchers to visually examine the magnetization states of single domain nanomagnets. However, MFM images have low signal to noise ration (SNR), which makes it difficult to estimate and collect qualitative results of the magnetization states of the nanomagnets in a nanomagnet array. The current practice is to visually estimate the state of the magnetic nanostructures from an MFM image, which can be a tedious process and is prone to variability from user to user, particularly as the dimensions of the magnetic nanostructures are reduced.
Accordingly, what is needed in the art is an image processing system that automatically estimates the magnetization states of patterned magnetic nanostructures based upon acquired MFM images of the patterned nanostructure.